1. Technical Field
The present disclosure relates to an AC impedance measuring device. More particularly, the present disclosure relates to the improvement of the measurement of AC impedance characteristics during the charge and discharge of a battery.
2. Related Art
In recent years, rechargeable secondary batteries have drawn attention in terms of the environment and costs. In the secondary battery research and development field, there is a demand for the measurement of impedance characteristics at a desired frequency with high accuracy.
FIG. 6 is a schematic diagram illustrating a structure for measuring the impedance of the secondary battery using an AC method. An oscillator 2 applies an AC signal to a secondary battery, which is a device under test (hereinafter, referred to as a “DUT”) 1, and a voltmeter 3 and an ammeter 4 measure the terminal voltage and current of the DUT 1, respectively. An amplitude ratio and a phase difference are calculated based on the measured values of the voltage and current. In this way, the impedance of the DUT 1 is calculated.
The calculated impedance of the DUT 1 has amplitude information and phase information and thus can be represented by a complex number. The impedance of the DUT 1 can be displayed as a point on a complex number plane in which the horizontal axis indicates a real number and the vertical axis indicates an imaginary number. In particular, a graph in which the polarity of the imaginary part is inverted and impedance at each frequency is plotted is called a Cole-Cole plot, which is generally used as an index for determining the internal characteristics or deterioration of the DUT 1 in, for example, the electrochemical field.
There is a method of performing Fourier transform on the measured voltage and current and obtaining the ratio thereof in order to calculate impedance at each frequency. In this case, the voltage and current are measured in a stable state without a transient response. When a voltage and current data cutout section (hereinafter, referred to as a “transformation window”) for Fourier transform is an integral multiple of the signal period, the impedance calculation result has no relation to the start phase of the transformation window and it is possible to accurately calculate impedance.
Even when the transformation window is not an integral multiple of the signal period, it is possible to reduce an error in the measurement of impedance by performing Fourier transform using sampling data with a period longer than the signal period or calculating impedance using a window function, such as a Harming window function or a Hamming window function.
JP-A-2007-265895 describes measuring impedance characteristics with only a DC component at a frequency f of almost 0 Hz (low frequency region), without measuring a response to an AC signal, thereby measuring the characteristics of a fuel cell at a high speed.
JP-A-2007-258661 describes using AC impedance measurement to evaluate a laminated ceramic capacitor in the manufacture of the laminated ceramic capacitor.
JP-A-2007-17405 describes using AC impedance measurement in the evaluation of the degree of rebar corrosion.
However, in the evaluation of the material characteristics, in order to measure impedance under the conditions that are as close to the actual use conditions as possible, it is necessary to measure the impedance in a state in which a constant current flows or there is a transient variation.
However, in the case of batteries or capacitors, when a constant current continuously flows, a terminal voltage is gradually changed due to, for example, the diffusion of ions, chemical reaction, and internal capacity.
When an AC signal is applied in the transient state, the output voltage of the DUT in which the AC signal is superimposed on the transient response is measured. When impedance is calculated using a value obtained by performing Fourier transform on the output voltage, the impedance includes an error due to the transient response.
There is a method which calculates an approximate expression of the transient response from the measured data using, for example, multiple regression analysis. However, in the method, it takes a long time to calculate the approximate expression and there is a large error in calculation.
When a window function, such as a Hanning window function or a Hamming window function, is used, measurement time longer than the signal period is required in order to reduce an error.
In addition, there is a method that shifts the phase of the transformation window once and calculates the influence of the transient response during Fourier transform based on an impedance difference. However, when the transient response cannot be linearly approximated, it is difficult to reduce an error.